A Visual Analytics Approach for Patient Stratification and Biomarker Discovery

dc.contributor.authorAlemzadeh, Shivaen_US
dc.contributor.authorKromp, Florianen_US
dc.contributor.authorPreim, Bernharden_US
dc.contributor.authorTaschner-Mandl, Sabineen_US
dc.contributor.authorBühler, Katjaen_US
dc.contributor.editorKozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgiaen_US
dc.date.accessioned2019-09-03T13:49:07Z
dc.date.available2019-09-03T13:49:07Z
dc.date.issued2019
dc.description.abstractWe introduce discoVA as a visual analytics tool for the refinement of risk stratification of cancer patients and biomarker discovery. Currently, tools for the joint analysis of multiple biological and clinical information in this field are insufficient or lacking. Our tool fills this gap by enabling bio-medical experts to explore datasets of cancer patient cohorts. By using multiple coordinated visualization techniques, nested visual queries on various data types can be performed to generate/prove a hypothesis by identifying discrete sub-cohorts. We demonstrated the utility of discoVA by a case study involving bio-medical researchers.en_US
dc.description.sectionheadersVisual Analytics in Medicine and Biology
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20191235
dc.identifier.isbn978-3-03868-081-9
dc.identifier.issn2070-5786
dc.identifier.pages91-95
dc.identifier.urihttps://doi.org/10.2312/vcbm.20191235
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20191235
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.8 [Computer Graphics]
dc.subjectApplications
dc.titleA Visual Analytics Approach for Patient Stratification and Biomarker Discoveryen_US
Files